Using VAST to inform the development regional environmental accounts
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Using VAST to inform the development regional environmental accounts

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Overview of how VAST might be used to inform the development of regional environmental accounts in Australia

Overview of how VAST might be used to inform the development of regional environmental accounts in Australia

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Using VAST to inform the development regional environmental accounts Presentation Transcript

  • 1. Using VAST to inform the developmentregional environmental accountsRichard ThackwayRegional Environmental Accounts Technical Workshop, ABS House, Belconnen, ACT24-25 June, 2013
  • 2. Outline• Concepts and definitions• What is VAST• VAST-2 methodology• VAST-2 case studies• Potential to use VAST for regional accounts• Where to from here?• More informationVAST = Vegetation Assets States and Transitions
  • 3. Land managers affect native veg conditionProcess:Land managers use land management practices (LMP) toinfluence ecological function at sites and the landscape by:• Modifying• Removing and replacing• Enhancing• Restoring• Maintaining• ImprovingPurpose/s:To achieve the desired mix of ecosystem services (space & time)
  • 4. VAST focuses on affects of land management onplant communitiesSoilVegetationRegenerative capacity/ functionVegetation structure &Species composition1. Soil hydrological status2. Soil physical status3. Soil chemical status4. Soil biological status5. Fire regime6. Reproductive potential7. Overstorey structure8. Understorey structure9. Overstorey composition10. Understorey compositionLMP are used to influence
  • 5. Condition and transformation - VAST• Change in a plant community (type) due to effects of landmanagement practices:– Structure– Composition– Regenerative capacity• Transformation = changes to vegetation condition over time• Condition and transformation are assessed relative to fullynatural a reference stateVegetation condition
  • 6. OccupationRelaxationAnthropogenic changeNet impactTime1800 1850 1900 1950 2000Based on Hamilton, Brown & Nolan 2008. FWPA PRO7.1050. pg 18Land use impacts on biodiversity and Life Cycle AnalysisReferenceModel of ecosystem change i.e. cause & effectChangeinvegetationindicatorodindex
  • 7. Vegetation Assets States and Transitions (VAST) frameworkVIVIVIIIIII0Native vegetationcoverNon-native vegetationcoverIncreasing modification caused by use and managementTransitions = trendVegetationthresholdsReference foreach veg type(NVIS)VAST - A framework for assessing & reportingvegetation conditionCondition statesResidual orunmodifiedNaturallybareModified Transformed Replaced -AdventiveReplaced -managedReplaced -removedThackway & Lesslie (2008) EnvironmentalManagement, 42, 572-90Diagnostic attributes of VAST states:• Vegetation structure• Species composition• Regenerative capacityNVIS
  • 8. Current datasets are snapshots but not time seriesThackway & Lesslie (2008)Environmental Management, 42, 572-90NB: Input dataset biophysical naturalness reclassified usingVAST framework/ replaced/ unmodifiedVAST 2009Veg condition derivedfrom classifying &mapping effects of landmanagement practicesNative
  • 9. VAST-2 System*Tracking change in vegetation condition* Thackway 2012 – VAST-2 handbook
  • 10. Conditioncomponents (3)[VAST]Attribute groups(10)[LUMIS]Description of loss or gain relative to pre settlement indicator reference state(22)Regenerativecapacity Fire regime 1. Area /size of fire foot prints2. Number of fire startsSoil hydrology 3. Soil surface water availability4. Ground water availabilitySoil physicalstate5. Depth of the A horizon6. Soil structureSoil nutrientstate7. Nutrient stress – rundown (deficiency) relative to soil fertility8. Nutrient stress – excess (toxicity) relative to soil fertilitySoil biologicalstate9. Recyclers responsible for maintaining soil porosity and nutrient recycling10. Surface organic matter, soil crustsReproductivepotential11. Reproductive potential of overstorey structuring species12. Reproductive potential of understorey structuring speciesVegetationstructureOverstoreystructure13. Overstorey top height (mean) of the plant community14. Overstorey foliage projective cover (mean) of the plant community15. Overstorey structural diversity (i.e. a diversity of age classes) of the standUnderstoreystructure16. Understorey top height (mean) of the plant community17. Understorey ground cover (mean) of the plant community18. Understorey structural diversity (i.e. a diversity of age classes) of the plantSpeciesCompositionOverstoreycomposition19. Densities of overstorey species functional groups20. Relative number of overstorey species (richness) of indigenous :exotic sppUnderstoreycomposition21. Densities of understorey species functional groups22. Relative number of understorey species (richness) of indigenous :exotic spp
  • 11. 131022DiagnosticattributesVegetationTransformationscoreAttributegroupsVegetationStructure(27%)Overstorey(3)Understorey(3)SpeciesComposition(18%)(2)UnderstoreyOverstorey(2)RegenerativeCapacity(55%)Fire(2)Reprodpotent(2)SoilHydrology(2)Biology(2)Nutrients(2)Structure(2) IndicatorsVAST-2 hierarchy
  • 12. Step 7Add the indices for the three components to generate total transformationindex for the ‘transformation site’ for each year of the historical record .Validate using Expert KnowledgeStep 1aUse a checklist of 22 indicators to compilechanges in LU & LMP* and plantcommunity responses over timeTransformation siteStep 1cEvaluate impacts on the plant communityover timeStep 1bEvaluate the influence of climate, soil andlandform on the historical recordStep 2Document responses of 22indicators over timeStep 4Document the referencestates for 22 indicatorsStep 3aLiterature review to determine thebaseline conditions for 22 indicatorsStep 3cCompile indicator data for 22indicators for reference siteStep 3bEvaluate the influence of climate, soiland landform for the reference siteReference state/sitesStep 5Score all 22 indicators for ‘transformation site’ relative to the‘reference site’. 0 = major change; 1 = no changeStep 6Derive weighted indices for the three components for the ‘transformationsite’ i.e. regenerative capacity (58%), vegetation structure (27%) andspecies composition (18%) by adding predefined indicatorsGeneral process for tracking changesVAST-2 system* LU Land useLMP Land management practices
  • 13. Importance of dynamicsRainfall assumed to be main driver of system dynamics• Period 1900 - 2013• Average seasonal rainfall (summer, autumn, …)• Rainfall anomaly is calculated above and below the mean• Two year running trend line fittedNB: Must calibrate remote sensing to account for dynamics• e.g ground cover, greenness and foliage projective cover
  • 14. WA WheatbeltBOM rainfallanomaly1900-2010(modelled 5 kmresolution)Derived frommonthlymodelledrainfall dataobtained fromhttp://www.longpaddock.qld.gov.au/silo/Rainfallanomalyrelative tomean
  • 15. Case studies VAST-2
  • 16. Case study 1• Region:Credo Station, Great Western Woodlands(GWW), WA• Reference state:Salmon Gum woodland overstorey , saltbush &bluebush understorey and ground layerMore info: http://www.vasttransformations.com/
  • 17. Photo: Harry RecherSalmon Gum reference state
  • 18. Case study 2Region:Taroom Shire, Brigalow Belt South, QldReference state:Brigalow woodland overstorey , mixed openshrubland understorey , grassy and forb groundlayerMore info: http://www.vasttransformations.com/
  • 19. Photo: Griffith UniversityBrigalow woodland reference state
  • 20. Wanaringa, Taroom Shire, QldVASTclasses
  • 21. Potential to use VAST-2 to produce wholelandscape regional accounts
  • 22. Potential to use VAST-2 forwhole landscape accountingIntegrated ecological classification (algorithm)• Scores and weights• Enables meaningful simplified reporting over timeRelevant ecological indicators (22)• Indicators designed to target key national datasets incl. several time seriesHistorical site-based records a basis for modeling &validating• Using GIS and remote sensing• Reference state
  • 23. List of VAST-2 indicators (22)Best sourcespatial dataTime series ormodeledYear/ RS source1. Area /size of fire foot prints TERN AusCover Time series (RS) >2000 MODIS2. Number of fire starts TERN AusCover Time series (RS) >2000 MODIS3. Soil surface water availability CSIRO Modeled epochs NA4. Ground water availability GA & CSIRO Modeled epochs NA5. Depth of the A horizon CSIRO Modeled epochs NA6. Soil structure CSIRO Modeled epochs NA7. Nutrient stress – rundown (deficiency) relative to soil fertility CSIRO Modeled epochs NA8. Nutrient stress – excess (toxicity) relative to soil fertility CSIRO Modeled epochs NA9. Recyclers responsible for maintaining soil porosity and nutrient recycling ?? Modeled epochs NA10. Surface organic matter, soil crusts CSIRO Modeled epochs NA11. Reproductive potential of overstorey structuring species CSIRO Modeled epochs NA12. Reproductive potential of understorey structuring species CSIRO Modeled epochs NA13. Overstorey top height (mean) of the plant community TERN AusCover Snap shot (RS) 2009 Alos/Landsat/ICESAT14. Overstorey foliage projective cover (mean) of the plant community TERN AusCover Time series (RS) 2000-10 Landsat15. Overstorey structural diversity (i.e. a diversity of age classes) of the stand TERN AusCover Snap shot (RS) 2009 Alos/Landsat/ICESAT16. Understorey top height (mean) of the plant community TERN AusCover Snap shot (RS) 2009 Alos/Landsat/ICESAT17. Understorey ground cover (mean) of plant community (fractional cover) TERN AusCover Time series (RS) 2000-10 Landsat18. Understorey structural diversity (i.e. a diversity of age classes) of the plant CSIRO Modeled epochs NA19. Densities of overstorey species functional groups (biomass) CSIRO Modeled epochs NA20. Relative number of overstorey species (richness) of indigenous :exotic spp CSIRO Modeled epochs NA21. Densities of understorey species functional groups (biomass) CSIRO Modeled epochs NA22. Relative number of understorey species (richness) of indigenous :exotic spp CSIRO Modeled epochs NA
  • 24. Monitoring Burnt Area and Approximate Day of BurnVAST-2 indicators 1 & 2http://data.auscover.org.au/xwiki/bin/view/Product+pages/BurntArea+DoB+MODIS+CDU
  • 25. 0204060801001985 1990 1995 2000 2005 2010YearFPCMonitoring Foliage Projective CoverVAST-2 indicator 14Source: Tim Danaher
  • 26. Overstorey height, cover & structural typesVAST-2 indicators 13, 14 & 15Source: Peter ScarthPolygons based on Landsat FPC (persistent green) and Allos radar backscatter at 25mVertical structure from IceSat . Mantuan Downs, Qld
  • 27. 1988 1991 199319952003 200420011999Monitoring Ground CoverVAST-2 indicator 17Source: Tim Danaher
  • 28. What about info for the other indicators?• Most info for these indicators are not dynamic e.g.– Most regenerative capacity indicators will requiremodels rather than remote sensing– Most species composition indicators will require expertelicitation modeling of site data
  • 29. Conclusions (1)• VAST is a useful accounting tool for tracking change andtrend in the condition of vegetated landscapes –– Change is due to use and management
  • 30. 012345671750 1800 1850 1900 1950 2000 2050X, Y Tas Midlands012345671750 1800 1850 1900 1950 2000 2050X, Y Tas Midlands012345671750 1800 1850 1900 1950 2000 2050X, Y Tas Midlands012345671750 1800 1850 1900 1950 2000 2050X, Y Tas Midlands012345671750 1800 1850 1900 1950 2000 2050X, Y Tas Midlands012345671750 1800 1850 1900 1950 2000 2050X, Y Tas Midlands02461750 1800 1850 1900 1950 2000 2050X, Y Tas Midlands02461750 1800 1850 1900 1950 2000 2050X, Y Tas MidlandsPotential transformationsWe can do this at sites
  • 31. 1962 1983 1986 1997 2004250 hectare ‘Talaheni’, Murrumbateman, NSWWe can monitor veg condition across smallareas e.g. propertiesVAST states
  • 32. Reporting condition states ‘Talaheni’0501001502002503001962 1983 1986 1997 2004Year of VAST assessmenthectares231323356VAST states
  • 33. 2009Source: http://app.monitor.abares.gov.au/map.htmlLegend20122014We cannot annualize monitoring of vegcondition whole landscapesRemoved managedRemoved replaced/unmodifiedVAST states
  • 34. Conclusions (2)• VAST also has value for:– Synthesizing information (quantitative and qualitative)– ‘Telling the story’ of landscape transformation– Engaging land managers and ecologists as equal players
  • 35. VAST helps in ‘telling the story’Residual/ unmodifiedModifiedTransformedAdventiveReplaced andmanagedReplaced /removedOrgan Pipes National Park –ex cropping paddockTrajectories ofvegetation statusand VAST classesreflect choicesand driversVASTclasses
  • 36. More informationhttp://www.vasttransformations.com/http://portal.tern.org.au/searchhttp://aceas-data.science.uq.edu.au/portal/Acknowledgements• University of Queensland, Department of Geography Planning andEnvironmental Management for ongoing research support• Many public and private land managers, land managementagencies, consultants and researchers have provided data and information